12 of 12 Permanent Statistical Modelling Jobs in the Thames Valley

in London. We are looking for an AI analytics engineer/data focused developer. You’ll join our London office to drive development of Savantiq’s analytics capabilities: from statistical modelling and custom ML models, to retrieval systems and fine-tuned LLMs. You’ll work directly with the CTO, shaping cutting-edge tools that transform deal-making in … seeking the right candidate, with c. 2-4 years of experience, to strengthen our position even further. The role is in person in London. Skills Core Solid foundation in statistical modelling and data-driven problem solving, with hands-on experience with a range of ML/AI techniques, e.g. supervised/unsupervised learning, natural language processing and LLMs. More ❯

Data Science, Artificial Intelligence, Mathematics, or a related field 🐍 Proficiency in Python and familiarity with libraries such as TensorFlow, PyTorch, or scikit-learn 🧩 Understanding of machine learning algorithms and statistical modelling 📈 Strong problem-solving and analytical mindset 🗣 Excellent communication skills and a genuine passion for learning Nice to Have: 💾 Experience with SQL, data pipelines , or cloud platforms ( AWS More ❯

Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines More ❯

under the guidance of senior team members. · Assist in extracting insights from large datasets to improve car performance and operational efficiency. · Contribute to the implementation of AI techniques and statistical models to solve complex engineering problems. · Collaborate with engineers across departments to understand requirements and deliver data-driven solutions. · Document and present findings clearly to technical and non-technical More ❯

career the that of a Data Scientist. This builds on the knowledge of the Data+ certification and enables you to demonstrate your knowledge in advanced data processing, cleaning, and statistical modelling concepts. You will demonstrate your knowledge of machine learning, industry trends and use of specialised data science applications. You will also apply mathematical and statistical methods More ❯

that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Act as a technical lead within project teams, mentoring mid-level data scientists … by measurable impact, not just model accuracy. Proven experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and client stakeholders Bachelor’s or Master’s degree in a quantitative More ❯

of experience in data analysis and ETL development. Strong proficiency in Teradata SQL and Informatica PowerCenter. Experience building and validating risk models using SAS and Python. Solid understanding of statistical techniques and risk modeling frameworks. Familiarity with data governance and compliance standards. Excellent problem-solving and communication skills. ABOUT CAPGEMINI Capgemini is a global business and technology transformation partner More ❯

support clients in interpreting analytical results. Build algorithms applicable across varied use cases and markets. Key Skills & Experience Strong experience interfacing directly with customers. Background in data science , including statistical modelling, machine learning, or applied analytics. Proficiency in Python for data analysis, modelling, and cloud application development. Exposure to automotive systems, electrification, or battery applications . Additional More ❯

support clients in interpreting analytical results. Build algorithms applicable across varied use cases and markets. Key Skills & Experience Strong experience interfacing directly with customers. Background in data science , including statistical modelling, machine learning, or applied analytics. Proficiency in Python for data analysis, modelling, and cloud application development. Exposure to automotive systems, electrification, or battery applications . Additional More ❯

effectively to both technical and non-technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics. Knowledge of advanced football metrics (possession value models highly desirable). A deep passion for football combined More ❯

across the business. Develop, improve, and maintain customer segmentation models to provide deep insights into the subscription base and inform Product/Marketing strategies. Utilise predictive analytics and retention modelling to forecast churn risk and customer behaviour, leveraging data science techniques. Collaborate with cross-functional teams , including marketing, finance, product and editorial, to ensure data-driven decision-making aligns … analytics, preferably in a subscription-based business . Strong commercial acumen , with the ability to translate data insights into business strategies. Advanced analytical and quantitative skills , with expertise in statistical analysis and predictive modeling. Proficiency in SQL, Python, or R , and experience with data visualization tools such as Power BI, Tableau, or Looker Studio. Excellent stakeholder management skills , with … Knowledge of data science and machine learning techniques applied to subscription-based businesses, including churn prediction and lifetime value modeling. Experience in customer segmentation, cohort analysis, and marketing mix modelling (MMM). Example projects The i Paper - POLARIS Dashboard build and automation, including the setting of the KPI's - which we settled on using the last 12 months averages. More ❯

fan engagement. If you're passionate about using advanced data science to drive real-world impact in sport, this is the role for you. Key Responsibilities Develop and apply statistical models and algorithms to analyse player performance, match outcomes, and tactical insights Collect, clean, and process football-related data from diverse sources Build clear, compelling visualizations and deliver insights … Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment … into actionable insights for coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for More ❯